Building Generative AI Solutions
- Offered byUDACITY
Building Generative AI Solutions at UDACITY Overview
Building Generative AI Solutions
at UDACITY
Gain the skills to build advanced AI systems with real-world impact
Duration | 3 weeks |
Total fee | ₹14,350 |
Mode of learning | Online |
Difficulty level | Advanced |
Official Website | Go to Website |
Credential | Certificate |
Building Generative AI Solutions at UDACITY Highlights
Building Generative AI Solutions
at UDACITY
- Earn a certificate after completion of the course
- Personalized Career Services
- Real-world projects
- Practical tips and industry best practices
- Unlimited submissions and feedback loops
- Unlimited access to top-rated courses
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Building Generative AI Solutions at UDACITY Course details
Building Generative AI Solutions
at UDACITY
Skills you will learn
What are the course deliverables?
Vectors
Retrieval-Augmented Generation
OpenAI API
LangChain
More about this course
In this course students will get hands-on with LangChain to develop adaptive language models, gaining the expertise to bring AI-driven solutions to life
With a focus on practical applications across industries, you’ll learn to create user-friendly AI solutions that truly stand out
By the end, you’ll be equipped to design innovative systems that redefine what’s possible, ready to apply your expertise wherever AI can make a difference
Building Generative AI Solutions at UDACITY Curriculum
Building Generative AI Solutions
at UDACITY
Introduction to Building Generative Apps
Building Solutions with Vector Databases
Developing Generative AI Solutions with LangChain
Project: Personalized Real Estate Agent
Building Generative AI Solutions at UDACITY Faculty details
Building Generative AI Solutions
at UDACITY
Valerie Scarlata
Valerie is a Sr. Technical Content Developer at Udacity who has developed and taught a broad range of computing curricula for multiple colleges and universities.
Chang She
Chang has nearly two decades of experience building and teaching data / ML tooling. He was the second major contributor to pandas, an adjunct at Columbia for introduction to data science, and ran engineering at TubiTV focusing on recommender systems.
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